SMEs are currently confronted with major challenges such as increasing uncertainty and volatility. In order to face these challenges, agility and digitalization can be
implemented. Both concepts ...bring about numerous opportunities and new competency requirements. Currently, there are few scientifically based, practical training courses that
focus on digitization and/or agility. The aim of this paper is to provide a roadmap for the development of the training concept. In this training, participants will be able to acquire
theoretical content on a learning platform in a flexible way and they will be able to apply this knowledge in a learning factory. Based on a literature overview, requirements for such
a training and the necessary skills in a digital, volatile business environment will be given.
Nowadays, production companies are facing an increasingly volatile environment. Due to increasing globalization, but also de-globalization, taking into consideration an internal production network is ...becoming more and more important for companies, all in order to be able to counteract in an agile way the uncertainties such as swings in the demand. Current production network planning procedures focus on (re-)locating decisions without delving into what happens inside the plants, neglecting the dynamics of production networks, following a rigid top-down approach during the configuration phase, and they do not integrate the effects of planning tasks at the factory level (tactical and operational planning). In order to be able to make strategic decisions with a well-founded database regarding the production network, the effects on the tactical and operational level must be considered in an iterative way during the strategic decision-making process. The aim of this research is to define the requirements for an approach to strategic production network planning, which considers the effects at the tactical and operational level in an iterative way, and to develop a process model, derived from the requirements, that in its five phases considers the deficiencies of the existing approaches.
The field of Augmented Reality (AR) has received increasing attention in recent years, as AR can be applied to a wide range of problems. The use of AR offers great potential, especially in the ...industrial sector. Among many applications in this area, one promising application is the augmentation of cognitive assistance systems. Much research has already been done on the development of augmented support systems but it is still lacking on how to transform existing assistance systems into an AR application. This paper focuses on this transformation and presents a process model that intends to support the migration or digitalization of existing support systems into an AR application. An experimental study validates the proposed approach and derives recommendations for action.
"Product Innovation" is a 7-month product development course, conducted at the Institute of Innovation and Industrial Management with international and interdisciplinary student teams. A close ...connection and interaction between industry, students and research has been an important part of this project-based learning course. Due to the COVID19 pandemic and the worldwide occurring lockdowns, students were not able anymore to interact and conduct their projects in the proven manner. Being in a critical phase of the project, the course concept had to be reorganized and transferred to online conduction by using computer supported collaboration work within a few days. Both observations and surveys were used to compare changes in student´s behaviour and results of the project. This paper will describe 1) the original situation and course concept, 2) show how the course was transformed to online conduction, 3) describe the observations made and 4) analyse how the students experienced the transformation.
Pressure to increase effectiveness and efficiency drives the product development process. The software industry has been using agile development approaches due to their advantages when coping with ...uncertainties and simultaneously increasing value. Therefore, the following work deals with the considerations of agile powertrain development. In order to identify important conditions for the incorporation of agile principles into powertrain development, semistructured interviews were conducted with experts from an engineering company. Having identified agile development challenges, advantages, and principles, the next step is comparing agile principles with the current principles of conventional powertrain development. Furthermore, a basic understanding of the powertrain development process regarding the incorporation of agile principles is established, the main attributes of powertrain development are investigated, and the key disciplines involved are identified. Finally, a model is created to assess whether the application of an agile or conventional development approach is more suitable.
Currently a paradigm shift in manufacturing industry is claimed. Driven by economic problems Industry 4.0 is hoped for being the solution to bringing back manufacturing to western economies. But ...especially SMEs tend to wait and see how this trend is developing. What is missing is a clear elaboration of Industry 4.0 specifically for SMEs. This paper elaborates the problems of SMEs with Industry 4.0 that mainly can be related to inherent characteristics like lack of resources. A procedure model is introduced, that mainly consists of 3 steps starting with an analysis of the status quo, where relevant data is gathered. Then KPIs are calculated that should further help to identify focus areas. Finally a decision based on the KPIs has to be made regarding the first steps towards Industry 4.0. This paper introduces the procedure model as well as a first draft of a criteria catalogue for deviating relevant KPIs.
In waste management, the assessment of CO2 emissions offers the possibility to evaluate and compare the environmental impact of different waste treatment processes. Here, we compare the performance ...of waste incineration with alternative thermal treatment scenarios and recycling scenarios to the primary production of materials to analyze the respective CO2 emissions. The aim is to determine whether thermal and material recycling of waste results in (net) CO2 surpluses or reductions, thus, showing whether it makes sense for climate ambitions to recover waste, thermally or materially. A case study of an internationally active waste management company in Austria is analyzed, conducting a life cycle assessment of its thermal and material waste recycling. On thermal waste treatment the core of the analysis is the comparison with primary energy sources. Using waste as an energy source, especially in cement plants and the paper industry, has proven to be an effective technology for reducing CO2 emissions. We also find current practices in material recycling to be of lower CO2 emissions than alternative primary material supply. Scaling results to the national level we find that for the case of Austria current waste management practices have the potential to save an equivalent of 2.6% of Austria's total CO2 emissions (all sectors) for thermal fractions and an equivalent of 1% for material recycling.
Display omitted
•CO2 emission impact of thermal waste treatment replacing fossils in basic industry.•CO2 emission impact of material waste recovery relative to primary production.•Quantification for full scale Central European waste management company.•Life Cycle Assessment to compare waste treatment methods.•Thermal and material recovery can reduce CO2 emissions significantly.
The Institute of Innovation and Industrial Management operates a learning factory (LeanLab) since 2014 to enhance academic education, company trainings and hands-on research in the fields of ...industrial engineering and logistics. The aim is to enable practice oriented learning in an environment close to industrial reality for facilitating effective knowledge-transfer. An extension with state of the art technologies relevant for future manufacturing sites is currently planned. Learning factories are suitable platforms for applying, testing and spreading technologies and should thus guarantee better and more targeted technology-development and transfer. Moreover, training sessions for workers will be designed to prepare them for the Industry 4.0 environment in the factory of the future. These trainings will focus on the development of the skills and qualifications necessary for workers to cope with the increasing complexity in industrial environments. This paper presents the actual state of the LeanLab and illustrates the next concrete steps towards an Industry 4.0 learning factory.
PurposeImproving productivity and efficiency has always been crucial for industrial companies to remain competitive. In recent years, the topic of environmental impact has become increasingly ...important. Published research indicates that environmental and economic goals can enforce or rival each other. However, few papers have been published that address the interaction and integration of these two goals.Design/methodology/approachIn this paper, we identify both, synergies and trade-offs based on a systematic review incorporating 66 publications issued between 1992 and 2021. We analyze, quantify and cluster examples of conjunctions of ecological and economic measures and thereby develop a framework for the combined improvement of performance and environmental compatibility.FindingsOur findings indicate an increased significance of a combined consideration of these two dimensions of sustainability. We found that cases where enforcing synergies between economic and ecological effects were identified are by far more frequent than reports on trade-offs. For the individual categories, cost savings are uniformly considered as the most important economic aspect while, energy savings appear to be marginally more relevant than waste reduction in terms of environmental aspects.Originality/valueNo previous literature review provides a comparable graphical treatment of synergies and trade-offs between cost savings and ecological effects. For the first time, identified measures were classified in a 3 × 3 table considering type and principle.
Empty storage shelves and long customer lead times due to a sharp rise in market demand from industries on the one hand (e.g., pharmaceutical products). On the other hand, increasing short-term ...working or unemployment due to a rapid decline in demand (e.g., automotive). Current supply and demand gaps caused by the COVID-19 pandemic remind us that successful competition in volatile business environments requires rapid adjustments of production capacities.
Capacity management (CM) addresses these adjustments by adapting production capacity to market demand. Operations managers of flexible manufacturing systems can adjust the capacity by using various levers (e.g., overtime, used machines, …). To guide these managers, decision support systems (DSS) exist for short-term CM (e.g., shop floor scheduling). However, due to complexity and runtime problems, the decision-making process for medium-term CM is usually carried out with low technical support.
Increases in computing power and advances in algorithm performance over the past decades have enabled Machine Learning to solve ever more complex problems such as the aforementioned issues. Reinforcement Learning (RL) in particular has shown good performance in solving short-term CM problems when compared to humans or other established heuristics.
In this work we review the current literature for CM using RL in flexible manufacturing systems. We identify an existing lack of knowledge within the overlap of medium-term CM and RL. However, good performance of RL in short-term CM indicates that an application in medium-term CM should be evaluated. In addition, we propose a concept of a method for medium-term CM based on RL to support operations managers in the decision-making process. The resulting DSS could have a significant impact on production performance, especially in terms of capacity adjustment speed.
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